jesse-uxandGrok (agent loop)
19379fbb41
研究章仍在六章之后、口径替换之前。独立年度方法参考仍在口径替换之后，来源说明不会被删掉。两条打回测试的替身补上额外参数，不改报告计算，不改原有断言。指纹记录改称 BUG-1430，因为 BUG-1429 已被研究章占用。 跑过两条打回测试、六章与指纹相关测试，以及 200 张英文扫描，退出码都是 0。 Co-Authored-By: Grok (agent loop)
123 lines
7.2 KiB
Python
123 lines
7.2 KiB
Python
"""Golden facts use deliberately fictional input, never a user birth record."""
|
|
import copy
|
|
import json
|
|
from pathlib import Path
|
|
|
|
from scripts.reader_dasha_applicability import BOUNDARY, render_dasha_applicability
|
|
from scripts.report_fact_table_contract import validate_fact_tables
|
|
|
|
ROOT = Path(__file__).resolve().parents[1]
|
|
|
|
|
|
def test_golden_applicability_never_relaxes_missing_or_inapplicable_families():
|
|
packet = json.loads((ROOT / "frontend/tests/fixtures/report-density-fictional-reader.json").read_text(encoding="utf8"))
|
|
original = copy.deepcopy(packet)
|
|
output = render_dasha_applicability(packet)
|
|
families = packet["worksheets"]["timing_and_predictive_systems"]["dasha_master_pack"]["families"]
|
|
assert len(families) == 15
|
|
assert output.count(BOUNDARY) == len(families) - 1 + 2
|
|
for key, value in families.items():
|
|
if key == "vimshottari":
|
|
assert "| Vimshottari |" not in output
|
|
continue
|
|
name = "Kala Chakra" if key == "kala_chakra" else key.replace("_", "-").title()
|
|
assert f"| {name} |" in output
|
|
if value.get("reason"):
|
|
from scripts.reader_dasha_applicability import REASON_LABELS
|
|
assert REASON_LABELS[value["reason"]] in output
|
|
assert value["reason"] not in output
|
|
assert all(name in output for name in ["Narayana", "Tribhagi-40", "Shattrimshatsama", "Satabdika", "Mudda", "Patyayini"])
|
|
assert "月宿与月相组合未满足该大运的适用条件" in output
|
|
assert "本地计算尚未提供可用周期" in output
|
|
assert packet == original
|
|
|
|
|
|
def test_golden_narayana_periods_and_readable_known_and_unknown_reasons():
|
|
packet = json.loads((ROOT / "frontend/tests/fixtures/report-density-fictional-reader.json").read_text(encoding="utf8"))
|
|
timing = packet["worksheets"]["timing_and_predictive_systems"]
|
|
assert len(timing["narayana_dasha"]["mahadasha_sequence"]) == 12
|
|
assert len(timing["narayana_dasha"]["dense_boundaries"]) == 156
|
|
output = render_dasha_applicability(packet)
|
|
narayana = next(line for line in output.splitlines() if line.startswith("| Narayana |"))
|
|
assert "本次已返回周期" in narayana
|
|
assert "这不代表已完成多引擎验证" in narayana
|
|
assert "缺少可核对周期" not in narayana
|
|
assert "本次计算未提供帕特雅伊尼年运周期" in output
|
|
assert "patyayini_dasha_missing" not in output
|
|
timing["annual_tajika_pack"]["patyayini_dasha"]["reason"] = "unknown_internal_reason_123 arbitrary English detail"
|
|
unknown = render_dasha_applicability(packet)
|
|
assert "暂无可核对的详细说明" in unknown
|
|
assert "unknown_internal_reason_123" not in unknown
|
|
assert "arbitrary English detail" not in unknown
|
|
|
|
|
|
def test_legacy_applicability_discloses_missing_evidence_without_guessing_families():
|
|
output = render_dasha_applicability({})
|
|
assert "缺少本次计算的结构化适用性证据" in output
|
|
assert BOUNDARY not in output
|
|
|
|
|
|
def test_full_golden_shared_markdown_is_byte_identical_and_reader_copy_is_clean():
|
|
from types import SimpleNamespace
|
|
from scripts.professional_report_reference import build_professional_report_reference
|
|
from scripts.reader_appendix_language import clean_reader_appendix_markdown
|
|
|
|
packet = json.loads((ROOT / "frontend/tests/fixtures/report-density-fictional-reader.json").read_text(encoding="utf8"))
|
|
raw = packet["markdown"]
|
|
engine = SimpleNamespace(build_professional_report_reference_packet=lambda *args, **_kwargs: packet, render_pl9_markdown=lambda value: raw)
|
|
handler = SimpleNamespace(_high_rigor_birth_payload=lambda body: {"year": 2000, "hour": 12, "minute": 0, "today": "2026-09-22"}, _compute_full_reading_for_thematic=lambda birth: {})
|
|
for include in (False, True):
|
|
result = build_professional_report_reference(handler, {"format": "markdown", "include_fact_tables": include}, engine=engine)
|
|
assert result["markdown"].encode("utf8") == raw.encode("utf8")
|
|
if include:
|
|
assert result["reader_dasha_applicability"] == packet["reader_dasha_applicability"]
|
|
clean = clean_reader_appendix_markdown(raw)
|
|
assert "pl9" in raw.lower()
|
|
assert "pl9" not in clean.lower()
|
|
assert len(clean.splitlines()) == len(raw.splitlines())
|
|
assert sum(line.startswith("|") for line in clean.splitlines()) == sum(line.startswith("|") for line in raw.splitlines())
|
|
for field in ("degree_in_sign", "sign_cn", "nakshatra_lord"):
|
|
assert clean.count(field) == raw.count(field)
|
|
|
|
|
|
def test_optional_table_validator_fails_closed_on_bad_shape():
|
|
errors = []
|
|
validate_fact_tables([{"id": "annual"}], lambda *error: errors.append(error))
|
|
assert errors
|
|
errors.clear()
|
|
validate_fact_tables([], lambda *error: errors.append(error))
|
|
assert not errors
|
|
|
|
|
|
def test_fact_subtable_contract_uses_golden_periods_and_keeps_legacy_snapshots():
|
|
import jsonschema
|
|
|
|
packet = json.loads((ROOT / "frontend/tests/fixtures/report-density-fictional-engine.json").read_text(encoding="utf8"))
|
|
source = "worksheets.timing_and_predictive_systems.dasha"
|
|
timeline = packet["worksheets"]["timing_and_predictive_systems"]["dasha"]["timeline"]
|
|
rows = [{"sourcePath": f"{source}.timeline[{index}]", "cells": [period["lord_cn"], period["start"], period["end"], f'{period["full_years"]:.2f}', "是" if period["is_current"] else "否"]} for index, period in enumerate(timeline)]
|
|
table = {"id": "vimshottari", "title": "Vimshottari 主运", "claimStatus": "parameter_sensitive", "sourcePath": source, "note": "原始计算供核对。", "columns": ["主运", "起", "止", "年数", "当前"], "rows": rows}
|
|
current_index, current = next((index, period) for index, period in enumerate(timeline) if period["is_current"])
|
|
child_source = f"{source}.timeline[{current_index}]"
|
|
child = {"id": "antardasha", "title": "当前主运下分运", "sourcePath": child_source, "note": "原始计算供核对。", "columns": ["分运", "起", "止", "当前"], "rows": [{"sourcePath": f"{child_source}.antardasha_timeline[{index}]", "cells": [period["lord_cn"], period["start"], period["end"], "是" if period["is_current"] else "否"]} for index, period in enumerate(current["antardasha_timeline"])]}
|
|
schema = json.loads((ROOT / "contracts/personal-report/report-document.v2.schema.json").read_text(encoding="utf8"))
|
|
contract = {"$ref": "#/definitions/factTable", "definitions": schema["definitions"]}
|
|
for candidate in [table, {**table, "subtables": [child]}]:
|
|
errors = []
|
|
validate_fact_tables([candidate], lambda *error: errors.append(error))
|
|
assert not errors
|
|
jsonschema.validate(candidate, contract)
|
|
for mutation in ("row_width", "origin", "duplicate", "unknown_key"):
|
|
invalid = copy.deepcopy({**table, "subtables": [child]})
|
|
if mutation == "row_width":
|
|
invalid["subtables"][0]["rows"][0]["cells"].pop()
|
|
elif mutation == "origin":
|
|
invalid["subtables"][0]["sourcePath"] = "worksheets.other"
|
|
elif mutation == "duplicate":
|
|
invalid["subtables"].append(copy.deepcopy(child))
|
|
else:
|
|
invalid["subtables"][0]["raw"] = True
|
|
errors = []
|
|
validate_fact_tables([invalid], lambda *error: errors.append(error))
|
|
assert errors, mutation
|